My primary research area is computer vision, closely integrated with applied machine learning and multimedia. The main focus of my current research is on designing learning algorithms that make the most effective use of contextual knowledge in presence of sparse and noisy data. Some examples are image and video annotation, large-scale visual recognition, web mining, social media analysis.

I have been invited to contribute to the panel “Deep Learning, Pattern Recognition and Vision, which direction?” during the CVPL day in Modena, Italy, on “Why is Deep Learning so cool?” [slides available online]. The event has been opened by Naftali Tishby with a very interesting talk about “Information Theory of Deep Learning”. A similar talk is also available on YouTube.

This 26 and 27 September 2017, I was involved in the kickoff event for European Researchers’ Night in Brussels #MSCAnight. With thousands of visitors, most of which were children, it was a smashing success! I have presented my research on machine learning and visual perception, and talked about visual illusions and teaching computers to see.

Our paper “Automatic Image Annotation via Label Transfer in the Semantic Space”, by T. Uricchio, myself, L. Seidenari and A. Del Bimbo, has been accepted for publication in Pattern Recognition and is now available online. It is an extended version of our KCCA-based tag propagation model presented in our ICMR’14 paper, containing more experiments and a novel tag denoising procedure.

A few days later, our paper “Learning without Prejudice: Avoiding Bias in Webly-Supervised Action Recognition” has been also accepted for publication in Computer Vision and Image Understanding (CVIU) and is now available online. Here we present a (fully) webly-supervised model for action recognition in videos. This is a joint work with F. Tombari and C. Rupprecht from TUM (Germany).

The University of Padova is one of Europe’s oldest and most prestigious seats of learning. The University of Padova is ranked first among Italian universities according to most international rankings (ARWU, US-News) and research evaluation agencies (ANVUR) [UniPD at a glance].

I have been selected Marie Curie Fellow of the week! Marie Sklodowska-Curie Actions (MSCA) Individual Fellowships are highly prestigious and competitive and are meant to support the best, most promising European researchers.

When given a single frame of the video, humans can not only interpret the content of the scene, but also they are able to forecast the near future. This ability is mostly driven by their rich prior knowledge about the visual world, both in terms of (i) the dynamics of moving agents, as well as (ii) the semantic of the scene. We exploit the interplay between these two key elements to predict scene-specific motion patterns.